We are looking for a Senior JavaScript Integration Software Engineer — a builder at heart and an AI-native thinker — to join our engineering team. In this role, you will design, develop, and own complex integration solutions that connect disparate systems, APIs, and data sources to deliver seamless digital experiences at scale.You will play a central role in shaping our data integration strategy, leveraging Databricks as a core platform for data engineering, analytics, and AI-driven workflows. As an AI-native engineer, you will go beyond traditional integration work — embedding intelligence into pipelines, automating decision points, and building systems that learn and adapt. You will collaborate closely with cross-functional teams — including product, architecture, data, and DevOps — to ensure integrations are robust, secure, and built for the future.

Responsibilities

Build & Integration Engineering

Take full ownership of building integrations end-to-end — from scoping and architecture through to deployment and production support
Design and build scalable integration solutions using JavaScript/Node.js, with a builder mindset focused on speed, quality, and impact
Connect enterprise systems, APIs, data platforms, and AI services into cohesive, reliable workflows
Evaluate and implement third-party tools, libraries, and integration platforms that accelerate delivery

Databricks & Data Integration

Design and implement data pipelines using Databricks, including Delta Lake, Databricks Workflows, and Unity Catalog
Integrate Databricks with upstream and downstream systems — ingesting data from APIs, SaaS tools, and operational databases into the lakehouse
Build and maintain ETL/ELT pipelines using PySpark or SQL within Databricks notebooks and jobs
Collaborate with data engineers and analysts to ensure data flowing through integrations is clean, governed, and ready for analytics and AI

AI-Native Engineering

Build integrations that incorporate AI and ML capabilities — including LLM APIs (e.g. OpenAI, Anthropic), model serving endpoints, and Databricks AI/ML features
Design event-driven and real-time pipelines that feed AI models with fresh, reliable data
Explore and implement agentic workflows, prompt orchestration, and AI-assisted automation within integration layers
Stay ahead of the curve on AI tooling and bring new capabilities into the team's engineering practice

API & Middleware Development

Design, build, and maintain RESTful and GraphQL APIs, webhooks, and event-driven integrations
Integrate enterprise systems including CRMs, ERPs, payment gateways, and third-party SaaS platforms
Develop and manage middleware, data transformation pipelines, and message queue systems (e.g. Kafka, RabbitMQ)
Build and maintain iPaaS workflows using platforms such as MuleSoft, Zapier, or custom solutions

Quality, Security & Observability

Write comprehensive unit, integration, and end-to-end tests to ensure reliability
Implement OAuth 2.0, API key management, and data encryption across all integration touchpoints
Instrument integrations with logging, monitoring, and alerting (e.g. Datadog, New Relic, or ELK stack)
Troubleshoot and resolve complex integration failures and performance bottlenecks in production

Collaboration & Communication

Partner with product managers, data teams, and stakeholders to translate business requirements into technical solutions
Produce clear technical documentation including API specs, data flow diagrams, and runbooks
Mentor mid-level and junior engineers and contribute to engineering standards and best practices
Participate actively in Agile ceremonies including sprint planning, standups, and retrospectives

Experience and education

Experience

Required

7+ years of professional software engineering experience with a strong focus on JavaScript and Node.js
5+ years of hands-on experience designing and building API integrations (REST, GraphQL, SOAP, webhooks)
Proven experience with Databricks or a comparable data platform (Apache Spark, Delta Lake, or similar lakehouse architectures)
Demonstrated experience building or integrating AI/ML services, including LLM APIs or model inference endpoints
Strong command of TypeScript and modern JavaScript (ES2020+), including async/await and event-driven patterns
Experience with cloud platforms (AWS, Azure, or GCP) and serverless architectures
Experience with containerisation and orchestration tools such as Docker and Kubernetes
Solid understanding of authentication and authorisation protocols: OAuth 2.0, JWT, SAML, OpenID Connect
Track record of working with message brokers and streaming platforms (Kafka, RabbitMQ, AWS SQS/SNS)

Preferred

Hands-on experience with Databricks AI/ML features including MLflow, Model Serving, and Feature Store
Experience with prompt engineering, LangChain, or agentic AI frameworks
Background in CI/CD pipeline setup and infrastructure-as-code (Terraform, CloudFormation)
Familiarity with data transformation tools and formats: JSON Schema, Avro, Protobuf, XML/XSLT
Experience with iPaaS platforms such as MuleSoft, Boomi, or Workato
Experience in regulated industries (fintech, healthcare, e-commerce) is highly advantageous

Education

The following qualifications are accepted for this role:

Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Technology, or a closely related field
Bachelor's degree in a non-technical discipline combined with a recognised software engineering or data bootcamp and a strong portfolio of integration or data projects
Associate's degree with 9+ years of directly relevant, progressively senior integration engineering experience
No formal degree with 10+ years of demonstrated senior-level integration and data engineering experience and a compelling portfolio

Certifications (Advantageous)

Databricks Certified Data Engineer Associate or Professional
Databricks Certified Machine Learning Associate
AWS Certified Developer – Associate or Professional
MuleSoft Certified Developer or Integration Architect
Google Professional Cloud Developer
Microsoft Certified: Azure Developer Associate